Multiple non linear regression model for the maximum number of migratory bird types during migration years

Since many years scientists have carried out researches about bird migration, but due to the large number of bird types estimated at around 10,000 in the world, it is not easy to predict the maximum number of migratory bird types through limited number of migration years. In this study, a multiple non linear regression model of maximum number probability function of migratory bird types has been obtained and can be used in the prediction of the maximum number of migratory bird types during any migration years.     

Estimation of cyclic long-memory parameters

This paper studies cyclic long-memory processes with Gegenbauer-type spectral densities. For a semiparametric statistical model, new simultaneous estimates for singularity location and long-memory parameters are proposed. This generalized filtered method-of-moments approach is based on general filter transforms that include wavelet transformations as a particular case. It is proved that the estimates are almost surely convergent to the true values of parameters. Solutions of the estimation equations are studied, and adjusted statistics are proposed. Monte-Carlo study results are presented to confirm the theoretical findings.     

Estimating Percentiles of Time-to-Failure Distribution Obtained from a Linear Degradation Model Using Kernel Density Method

In this article, we propose a nonparametric estimator for percentiles of the time-to-failure distribution obtained from a linear degradation model using the kernel density method. The properties of the proposed kernel estimator are investigated and compared with well-known maximum likelihood and ordinary least squares estimators via a simulation technique. The mean squared error and the length of the bootstrap confidence interval are used as the basis criteria of the comparisons. The simulation study shows that the performance of the kernel estimator is acceptable as a general estimator. When the distribution of the data is assumed to be known, the maximum likelihood and ordinary least squares estimators perform better than the kernel estimator, while the kernel estimator is superior when the assumption of our knowledge of the data distribution is violated. A comparison among different estimators is achieved using a real data set.     

A Simple Method to Ensure Plausible Multiple Imputation for Continuous Multivariate Data

Multiple Imputation (MI) is an established approach for handling missing values. We show that MI for continuous data under the multivariate normal assumption is susceptible to generating implausible values. Our proposed remedy, is to: (1) transform the observed data into quantiles of the standard normal distribution; (2) obtain a functional relationship between the observed data and it's corresponding standard normal quantiles; (3) undertake MI using the quantiles produced in step 1; and finally, (4) use the functional relationship to transform the imputations into their original domain. In conclusion, our approach safeguards MI from imputing implausible values.     

Additive Regression Model for Continuous Time Processes

In the setting of additive regression model for continuous time process, we establish the optimal uniform convergence rates and optimal asymptotic quadratic error of additive regression. To build our estimate, we use the marginal integration method.     

The Weibull–Dagum distribution: Properties and applications

ABSTRACT

In this article, we define a new lifetime model called the Weibull–Dagum distribution. The proposed model is based on the Weibull–G class. It can also be defined by a simple transformation of the Weibull random variable. Its density function is very flexible and can be symmetrical, left-skewed, right-skewed, and reversed-J shaped. It has constant, increasing, decreasing, upside-down bathtub, bathtub, and reversed-J shaped hazard rate. Various structural properties are derived including explicit expressions for the quantile function, ordinary and incomplete moments, and probability weighted moments. We also provide explicit expressions for the Rényi and q-entropies. We derive the density function of the order statistics as a mixture of Dagum densities. We use maximum likelihood to estimate the model parameters and illustrate the potentiality of the new model by means of a simulation study and two applications to real data. In fact, the proposed model outperforms the beta-Dagum, McDonald–Dagum, and Dagum models in these applications.     

Understanding microfascism: reading Deleuze and Guattari alongside management guru texts

ABSTRACT

The ‘management guru’ text has long been a source of interest for academic audiences. In this tradition, this paper argues that the content and underpinning ideology of the guru guide hold important insights for organizational scholars interested in the works of Gilles Deleuze and Felix Guattari (and vice versa). Specifically, this paper will demonstrate that a close reading of entrepreneur and guru, Tim Ferriss’s, Tools of Titans, can provide meaningful exegesis and development of the concept of ‘microfascism’ presented by Deleuze and Guattari across their shared and independent corpuses. Building upon extant organization studies literature, this paper will endeavour to contribute to the commentary on the management guru by suggesting that the desire for fascism, power, conformity, and rule-following of which Deleuze and Guattari speak offers a productive way of understanding the success of the management guru and the broader allure of the management advice industry.     

Multiple Migration and Use of Ties: Bangladeshis in Italy and Beyond

This article analyses previous multiple migratory trajectories of Bangladeshi first generation migrants before their arrival in Italy and within Italy. It also uncovers the role of social networks and transnational ties in their multiple migrations. The findings show that their first international migration was mainly shaped by their family’s socio-economic condition and transnational kinship networks. They already had someone from their family or close relatives in the preferred country with whom they were connected. Their onward relocations until arriving in Italy, in most cases, was to achieve the socio-economic success and legal status that they had failed to attain in their first and subsequent destinations, but the transnational connections with friends or acquaintances are a key resource facilitating these remigrations. Bangladeshis who arrived in Italy from various countries mostly had networks, either with someone from their local district in Bangladesh or with their earlier fellow migrants who moved to Italy before them.